Kepler shuffle for real-world flood simulations on GPUs

Abstract

We present a new graphics processing unit implementation of two second-order numerical schemes of the shallow water equations on Cartesian grids. Previous implementations are not fast enough to evaluate multiple scenarios for a robust, uncertainty-aware decision support. To tackle this, we exploit the capabilities of the NVIDIA Kepler architecture. We implement a scheme developed by Kurganov and Petrova (KP07) and a newer, improved version by Horváth et al. (HWP14). The KP07 scheme is simpler but suffers from incorrect high velocities along the wet/dry boundaries, resulting in small time steps and long simulation runtimes. The HWP14 scheme resolves this problem but comprises a more complex algorithm. Previous work has shown that HWP14 has the potential to outperform KP07, but no practical implementation has been provided. The novel shuffle-based implementation of HWP14 presented here takes advantage of its accuracy and performance capabilities for real-world usage. The correctness and performance are validated on real-world scenarios.